Text analysis approach for identifying psychological characteristics (with aggressiveness as an example)


Smirnoff I. Kuznetsova Y. Chudova N. Kovalyov A. Stankevich M.


The purpose of the study: to test the capabilities of a new automatic text analysis tool for identifying text parameters specific to people with certain psychological characteristics; to obtain data on the signs that distinguish texts of people with high personal aggressiveness. Method: a corpus linguistic-statistical research tool was applied, based on the relational-situational analysis, psycholinguistic indicators and dictionaries covering the vocabulary of emotional and rational evaluation; to assess the level of aggressiveness, the Bass-Perry questionnaire was used; the data were processed by binary classification algorithms: support vector machine (SVM) and Random Forest.Results: thanks to new tool, several textual signs of the authors' psychological characteristics were identified; classification was improved through the use of our data processing method; and some syntactic, semantic and lexical features of texts of highly hostile persons have been identified.

External links

DOI and a PDF link (in Russian) simultaneously: https://doi.org/10.21681/2311-3456-2019-4-72-79

The contents of the 4th issue of the Cybersecurity Issues journal: https://cyberrus.com/%E2%84%96-4-32/?lang=en

ResearchGate: https://www.researchgate.net/publication/335253320_Text_Analysis_Approach_for_Identifying_Psychological_Characteristics_with_Aggressiveness_as_an_Example

Read at CyberLeninka (in Russian): https://cyberleninka.ru/article/n/metody-vyyavleniya-po-tekstu-psihologicheskih-harakteristik-avtora-na-primere-agressivnosti

Semantic Scholar: https://api.semanticscholar.org/CorpusID:202245111

Reference link

Kovalev A. K., Kuznetsova Y. M., Minin A. N., Penkina M. Y., Smirnov I. V., Stankevich M. A., Chudova N. V. Text analysis approach for identifying psychological characteristics (with aggressiveness as an example) // Cybersecurity issues. – 2019. – No. 4. – Page 72-79.